Seamless R and C++ Integration with Rcpp

By Dirk Eddelbuettel. 2013

483 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Control and Systems Engineering, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/5fd09b7c68089cdf62c9f3a9cd2b2763fbf0a569

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Citations in the corpus

Biips: Software for Bayesian Inference with Interacting Particle Systems (2014, methodology): “Rbiips uses the Rcpp library (Eddelbuettel and François 2011; Eddelbuettel 2013).”
Rcpp: Seamless R and C++ Integration (2011, background): “The ‘Writing R Extensions’ manual (R Development Core Team, 2009a) describes in detail how to augment R with compiled code, focussing mostly on the C language.”
GGIR: A Research Community–Driven Open Source R Package for Generating Physical Activity and Sleep Outcomes From Multi-Day Raw Accelerometer Data (2019, methodology): “Most of the code is written in R, with a small part in C ++ needed for reading the binary data from the AX3 accelerometer brand using R package Rcpp as a dependency (Eddelbuettel, 2013).”
Detection of change in the spatiotemporal mean function (2017, methodology): “Algorithm 2 was applied in Section 5 by using the Rcpp package; Eddelbuettel and François (2013). Using our R package for this procedure, the application took approximately 6 min on an Intel 2.”
Simple Features for R: Standardized Support for Spatial Vector Data (2018, background): “Special thanks go to Dirk Eddelbuettel, for developing Rcpp (Eddelbuettel et al., 2011; Eddelbuettel, 2013).”
RcppArmadillo: Accelerating R with high-performance C++ linear algebra (2014, methodology): “Various matrix decompositions, linear program solvers, and 1This vignette corresponds to a paper published in Computational Statistics and Data Analysis.”
Introduction to stream: An Extensible Framework for Data Stream Clustering Research with R (2017, methodology): “9GHz and 8GB of memory, and the algorithm is implemented as a mixture of R and C++ code using the Rcpp interface package (Eddelbuettel and François 2011; Eddelbuettel 2013).”
Orchestrating single-cell analysis with Bioconductor (2019, methodology): “Two notable examples are the Rcpp [161–163] package for integrating C++ compiled code into R and the reticulate [164] package for interfacing with Python.”
A multivariate mixed hidden Markov model for blue whale behaviour and responses to sound exposure (2017, methodology): “First, we wrote the HMM forward algorithm using the Rcpp package [Eddelbuettel (2013)], which provides a simple way to use C++ code in conjunction with R software.”
R/qtl2: Software for Mapping Quantitative Trait Loci with High-Dimensional Data and Multiparent Populations (2018, unknown): “…is written in R, but computationally intensive aspects are written in C++. (Computationally intensive aspects of R/qtl1 are in C.) We use Rcpp (Eddelbuettel and François 2011; Eddelbuettel 2013) for the interface between R and C++, to simplify code and reduce the need for copying data in memory.”